• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1043-1060
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• 2023

An acceleration of climate change in recent years has led to increased attention towards 'blue carbon' which refers to the carbon captured by the ocean. However, our comprehension of marine ecosystems is still incomplete. This study classified and analyzed global marine eco-provinces using k-means clustering considering carbon cycling. We utilized five input variables during the past 20 years (2001-2020): Carbon-based Productivity Model (CbPM) Net Primary Production (NPP), particulate inorganic and organic carbon (PIC and POC), sea surface salinity (SSS), and sea surface temperature (SST). A total of nine eco-provinces were classified through an optimization process, and the spatial distribution and environmental characteristics of each province were analyzed. Among them, five provinces showed characteristics of open oceans, while four provinces reflected characteristics of coastal and high-latitude regions. Furthermore, a qualitative comparison was conducted with previous studies regarding marine ecological zones to provide a detailed analysis of the features of nine eco-provinces considering carbon cycling. Finally, we examined the changes in nine eco-provinces for four periods in the past (2001-2005, 2006-2010, 2011-2015, and 2016-2020). Rapid changes in coastal ecosystems were observed, and especially, significant decreases in the eco-provinces having higher productivity by large freshwater inflow were identified. Our findings can serve as valuable reference material for marine ecosystem classification and coastal management, with consideration of carbon cycling and ongoing climate changes. The findings can also be employed in the development of guidelines for the systematic management of vulnerable coastal regions to climate change.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.63-65
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• 2003

The purpose of the study is to produce the surface ground temperature diagnostically using surface EBM with the use of GRID model in Geographic Information Systems (GIS). Certain characteristics have been analyzed for local slope effect, coastal effect and influence of high orographic aspect on the surface ground temperature. We present discussions on the meteorological responsibility for their temperature. The derived surface ground temperatures can be provided for comparison with those from satellite-based observ ation.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.1-8
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• 1999

The estimation technique of surface water temperature by satellite remote sensing has been applied to ocean and large lakes using AVHRR. However, the spatial resolution AVHBR is not abquate for coastal region and small lakes. Landsat 5 TM has 120 m spatial resolution, which suits better. We carried out analysis of surface water temperature in Lake Sihwa and near coastal area using Landsat 5 TM. To relate digital number to the brightness temperature, we applied Empirical, NASA, RESTEC, Quadratic methods. Comparing calculated and observed value, we obtained as follows; NASA method, $R^2=0.9343$, RMSE(Root Mean Square Error)=3.5876$^{\circ}C$; RESTEC method, $R^2=0.8937$, RMSE=3.76$^{\circ}C$; Quadratic method, $R^2=0.8967$, RMSE=2.949$^{\circ}C$. Because Landsat TM has only one band for extracting surface temperature, it was difficult to correct for the atmospheric errors. For improving the accuracy of surface temperature detection using Landsat TM, there is a need for a method to decrease the effect of atmospheric contents.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.221-234
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• 2016

In Korea, most industrial parks and major cities are located in coastal areas, which results in serious environmental problems in both coastal land and ocean. In order to effectively manage such problems especially in coastal ocean, water quality should be monitored. As there are many factors that influence water quality, the Korean Government proposed an integrated Water Quality Index (WQI) based on in situmeasurements of ocean parameters(bottom dissolved oxygen, chlorophyll-a concentration, secchi disk depth, dissolved inorganic nitrogen, and dissolved inorganic phosphorus) by ocean division identified based on their ecological characteristics. Field-measured WQI, however, does not provide spatial continuity over vast areas. Satellite remote sensing can be an alternative for identifying WQI for surface water. In this study, two schemes were examined to estimate coastal WQI around Korea peninsula using in situ measurements data and Geostationary Ocean Color Imager (GOCI) satellite imagery from 2011 to 2013 based on machine learning approaches. Scheme 1 calculates WQI using estimated water quality-related factors using GOCI reflectance data, and scheme 2 estimates WQI using GOCI band reflectance data and basic products(chlorophyll-a, suspended sediment, colored dissolved organic matter). Three machine learning approaches including Random Forest (RF), Support Vector Regression (SVR), and a modified regression tree(Cubist) were used. Results show that estimation of secchi disk depth produced the highest accuracy among the ocean parameters, and RF performed best regardless of water quality-related factors. However, the accuracy of WQI from scheme 1 was lower than that from scheme 2 due to the estimation errors inherent from water quality-related factors and the uncertainty of bottom dissolved oxygen. In overall, scheme 2 appears more appropriate for estimating WQI for surface water in coastal areas and chlorophyll-a concentration was identified the most contributing factor to the estimation of WQI.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.5
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• pp.419-425
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• 2009

Although earthquake damage was negligible in Korea during the last a few decades, its historic records suggest that the peninsula have experienced severe earthquake damages throughout the history. The potential for disastrous earthquakes, therefore, should always be considered. Harbors handle 99.6% of imported and exported cargo in Korea. Thus, it is necessary to secure the safety of harbors against seismic events and to establish a support system of emergency measures. Although instrumental seismic data are favored for seismic hazard estimation, their history in the peninsula is limited only to the past 30 years, which does not represent the long-term seismic characteristics of the peninsula. We use historic earthquakes with magnitude greater than 5 to observe long-term regional seismic hazards. Results of historic earthquake records indicate relatively high seismic hazard at harbors in Pohang, Ulsan and Incheon. Analysis of instrumental earthquake records reveal relatively high seismic hazard for harbors located along the East coast including Okgye, Mukho, Donghae, Samcheok, Pohang, and Ulsan.

• Korean Journal of Remote Sensing
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• v.5 no.1
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• pp.57-67
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• 1989

This study on the southern coastal waters of Korea has been made by analysis of NOAA image and oceanographic observation data from October 1987 to August 1988. The results obtained from the study are as follow: Horizontal distributions of water temperature in different layers in winter ranged from 6.07 to 18.62$^{\circ}C$ at 0m layer, 6.02 to 18.54$^{\circ}C$ at 30m layer and 7.19 to 18.69$^{\circ}C$ at 50m layer. Consequently its vertical distribution showed homogeneity. Horizontal water temperature gradients were 0.28$^{\circ}C$/mile between the coastal waters and Tsushima warm waters. In summer, its horizontal distribution varied from 19.37 to 29.92$^{\circ}C$ at 0m layer, 13.26 to 27.11$^{\circ}C$ at 30m layer and 7.36 to 26.6$0^{\circ}C$ at 50m layer, and its vertical profile showed stratified structure. Vertical water temperature gradients were 0.44$^{\circ}C$/m between 30 and 50m layers. It was remarkable that distribution of southern coastal water system analysed by NOAA image coincided with relatively the oceanographic observation data but SST from NOAA image seemed to be 2-4$^{\circ}C$ lower in winter and 4-6$^{\circ}C$ lower in summer than the oceanographic data.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.571-580
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• 2010

Coastal shoreline movement due to erosion and deposition is a major concern for coastal zone management. Shoreline is changed by nature factor or development of coastal. Change of shoreline is threatening marine environment and destroying. Therefore, we need monitoring of shoreline change with time series analysis for coastal zone management. In this study, we analyzed the shoreline change using airphotograph, LiDAR and satellite imagery from 1971 to 2009 in Uljin, Gyeongbuk, Korea. As a result, shoreline near of the nuclear power plant show linear pattern in 1971 and 1980, however the pattern of shoreline is changed after 2000. As a result of long-term monitoring, shoreline pattern near of the nuclear power plant is changed by erosion toward sea. The pattern of shoreline near of KORDI until 2003 is changed due to deposition toward sea, but the new pattern toward land is developed by erosion from 2003 to 2009. The shoreline is changed by many factors. However, we will guess that change of shoreline within study area is due to construction of nuclear power plant. In the future work, we need sedimentary and physical studies.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1589-1597
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• 2021

Submarine groundwater discharge (SGD) in coastal areas is gaining importance as a major transport route that bring nutrients and trace metals into the ocean. This paper describes the analysis of the seasonal changes and spatiotemporal characteristicsthrough the modeling monthly SGD for 35 years from 1986 to 2020 for the Nakdong river basin. In this study, we extracted 210 watersheds and SGD estimation points using the SRTM (Shuttle Radar Topography Mission) DEM (Digital Elevation Model). The average annual SGD of the Nakdong River basin was estimated to be 466.7 m²/yr from the FLDAS (Famine Early Warning Systems Network Land Data Assimilation System) recharge data of 10 km which is the highest resolution global model applicable to Korea. There was no significant time-series variation of SGD in the Nakdong river basin, but the concentrated period of SGD was expanded from summer to autumn. In addition, it was confirmed that there is a large amount of SGD regardless of the season in coastal area nearby large rivers, and the trend has slightly increased since the 1980s. The characteristics are considered to be related to the change in the major precipitation period in the study area, and spatially it is due to the high baseflow-groundwater in the vicinity of large rivers. This study is a precedentstudy that presents a modeling technique to explore the characteristics of SGD in Korea, and is expected to be useful as foundational information for coastal management and evaluating the impact of SGD to the ocean.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.95-100
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• 2006

Measurements of ocean color from space since 1970s provided vital information with reference to physical and biogeochemical properties of the oceanic waters. The utility of these data has been explored in order to map and monitor highly toxic/or harmful algal blooms (HABs) that affected most of coastal waters throughout the world due to accelerated eutrophication from human activities and certain oceanic processes. However, the global atmospheric correction and bio-optical algorithms developed for oceanic waters were found to yield false information about the HABs in coastal waters. The present study aimed to evaluate the potential use of red tide index (RI) method, which has been developed by Ahn and Shanmugam (2005), for mapping of HABs in Korean and neighboring waters. Here we employed the SSMM to remove the atmospheric effect in the SeaWiFS image data and the achieved indices by RI method were found more appropriate in correctly identifying potential areas of the encountered HABs in Korean South Sea (KSS) and Chinese coastal waters during 1999-2004. But the existence of high absorbing and scattering materials greatly interfered with the standard OC4 algorithm which falsely identified red tides in these waters. In comparison with other methods, the RI approach for the early detection of HABs can provide state managers with accurate identification of the extent and location of these blooms as a management tool.

• Ocean Science Journal
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• v.41 no.2
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• pp.97-104
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• 2006

A useful radiance-converting method was developed to convert the Landsat-7 ETM+thermal-infrared (TIR) band's radiance ($L_{{\lambda},L7/ETM+}$) to that of Landsat-5 TM TIR ($L_{{\lambda},L5/TM+})$ as: $L_{{\lambda},L5/TM}=0.9699{\times}L_{{\lambda},L7/ETM+}+0.1074\;(R^2=1)$. In addition, based on the radiance-converting equation and the linear relation between digital number (DN) and at-satellite radiance, a DN-converting equation can be established to convert DN value of the TIR band between Landsat-5 and Landsat-7. Via this method, it is easy to integrate Landsat-5 and Landsat-7 TIR data to retrieve the sea surface temperature (SST) in coastal waters on the basis of local empirical algorithms in which the radiance or DN of Lansat-5 and 7 TIR band is usually the only input independent variable. The method was employed in a local empirical algorithm in Daya Bay, China, to detect the thermal pollution of cooling water discharge from the Daya Bay nuclear power station (DNPS). This work demonstrates that radiance conversion is an effective approach to integration of Landsat-5 and Landsat-7 data in the process of a SST retrieval which is based on local empirical algorithms.